Algorithm Based on Multiple Features for Recognition of E.coli Promoter Region

Abstract:

A promoter plays an important role in the transcription of DNA sequences; its recognition is very significant. This paper concerns about the problem of extracting information from a given DNA region and to make predictions whether it contains a promoter. We incorporate three types of information to access the significance of a promoter, information on content and information on structure, and then these information are used in a trained nonlinear classifier. The results show that our method performs well and achieve 13.4% average error rate on positive and negative data from non-coding regions and 17.0% average error rate on positive and negative data from coding regions.

• Periodical: Applied Mechanics and Materials (Volumes 48-49)
• Pages: 164-169
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.48-49.164
• Online since: February 2011
• Authors: Wei Ao, Jie Yang, Wan Qin Xiang, Xiao Jun Liu
• Keywords: Binding Motif, Nonlinear Classifier, Promoter, Viterbi Algorithm, Word Frequency

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